[V. Gray]

I'm just using the example vision code, with a few minor alterations to get it to work.

package edu.wpi.first.wpilibj.templates;

import edu.wpi.first.wpilibj.Joystick;
import edu.wpi.first.wpilibj.SimpleRobot;
import edu.wpi.first.wpilibj.Timer;
import edu.wpi.first.wpilibj.camera.AxisCamera;
import edu.wpi.first.wpilibj.camera.AxisCameraException;
import edu.wpi.first.wpilibj.image.BinaryImage;
import edu.wpi.first.wpilibj.image.ColorImage;
import edu.wpi.first.wpilibj.image.CriteriaCollection;
import edu.wpi.first.wpilibj.image.NIVision.MeasurementType;
import edu.wpi.first.wpilibj.image.NIVisionException;
import edu.wpi.first.wpilibj.image.ParticleAnalysisReport;
import edu.wpi.first.wpilibj.image.RGBImage;
import edu.wpi.first.wpilibj.smartdashboard.SmartDashboard;

/**
 * Sample program to use NIVision to find rectangles in the scene that are illuminated
 * by a red ring light (similar to the model from FIRSTChoice). The camera sensitivity
 * is set very low so as to only show light sources and remove any distracting parts
 * of the image.
 * 
 * The CriteriaCollection is the set of criteria that is used to filter the set of
 * rectangles that are detected. In this example we're looking for rectangles with
 * a minimum width of 30 pixels and maximum of 400 pixels. Similar for height (see
 * the addCriteria() methods below.
 * 
 * The algorithm first does a color threshold operation that only takes objects in the
 * scene that have a significant red color component. Then removes small objects that
 * might be caused by red reflection scattered from other parts of the scene. Then
 * a convex hull operation fills all the rectangle outlines (even the partially occluded
 * ones). Finally a particle filter looks for all the shapes that meet the requirements
 * specified in the criteria collection.
 *
 * Look in the VisionImages directory inside the project that is created for the sample
 * images as well as the NI Vision Assistant file that contains the vision command
 * chain (open it with the Vision Assistant)
 */
public class CameraTest extends SimpleRobot {
    
    AxisCamera camera;          // the axis camera object (connected to the switch)
    CriteriaCollection cc;      // the criteria for doing the particle filter operation
//    Joystick joystick = new Joystick(1);
    
    public void robotInit() {
        camera = AxisCamera.getInstance("10.38.81.11");  // get an instance ofthe camera
        cc = new CriteriaCollection();      // create the criteria for the particle filter
        cc.addCriteria(MeasurementType.IMAQ_MT_BOUNDING_RECT_WIDTH, 30, 400, false);
        cc.addCriteria(MeasurementType.IMAQ_MT_BOUNDING_RECT_HEIGHT, 40, 400, false);
    }

    public void autonomous() {
        while (isAutonomous() && isEnabled()) {
        	System.out.println("Custom Autonomous() method running, consider providing your own.");
            try {
                /**
                 * Do the image capture with the camera and apply the algorithm described above. This
                 * sample will either get images from the camera or from an image file stored in the top
                 * level directory in the flash memory on the cRIO. The file name in this case is "10ft2.jpg"
                 * 
                 */
                ColorImage image = camera.getImage();         // comment if using stored images
//                ColorImage image;                           // next 2 lines read image from flash on cRIO
//                image =  new RGBImage("/10ft2.jpg");
                BinaryImage thresholdImage = image.thresholdRGB(25, 255, 0, 45, 0, 47);   // keep only red objects
                BinaryImage bigObjectsImage = thresholdImage.removeSmallObjects(false, 2);  // remove small artifacts
                BinaryImage convexHullImage = bigObjectsImage.convexHull(false);          // fill in occluded rectangles
                BinaryImage filteredImage = convexHullImage.particleFilter(cc);           // find filled in rectangles
                
                ParticleAnalysisReport[] reports = filteredImage.getOrderedParticleAnalysisReports();  // get list of results
                for (int i = 0; i < reports.length; i++) {                                // print results
                    ParticleAnalysisReport r = reports[i];
                    System.out.println("Particle: " + i + ":  Center of mass x: " + r.center_mass_x);
                }
                System.out.println(filteredImage.getNumberParticles() + "  " + Timer.getFPGATimestamp());
                SmartDashboard.putInt("Number of Particles: ",filteredImage.getNumberParticles());

                /**
                 * all images in Java must be freed after they are used since they are allocated out
                 * of C data structures. Not calling free() will cause the memory to accumulate over
                 * each pass of this loop.
                 */
                filteredImage.free();
                convexHullImage.free();
                bigObjectsImage.free();
                thresholdImage.free();
                image.free();
                
        } 
                catch (AxisCameraException ex) {        // this is needed if the camera.getImage() is called
                ex.printStackTrace();
            } 
            catch (NIVisionException ex) {
                ex.printStackTrace();
            }
        }
    }

    /**
     * This function is called once each time the robot enters operator control.
     */
    public void operatorControl() {
//    	while(isOperatorControl() == true){
//        	System.out.println(camera);
//    	}
    }